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Field
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is modelling and optimization using molecular dynamics and machine learning. The position is part of a team looking at these fascinating systems from their fundamental properties and making them in
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Postdoc who, in addition to the desired expertise stated above, have the following skills and qualifications: A PhD degree in bioinformatics, machine learning, computational biology, statistical genetics
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the next generation of PV technologies for beyond 2030. The new postdoctoral research position will use materials modelling techniques (DFT, molecular dynamics, machine learning potentials) to investigate
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position within a Research Infrastructure? No Offer Description Samuel Kaski’s research group Probabilistic Machine Learning is searching for postdocs to work on AI fundamentals in exciting projects
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research, covering research topics including, but not limited to Crop Modeling, Machine Learning, Artificial Intelligence (AI), Internet of Things, and Big Data analysis for Precision and Prescriptive
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TAMU. Experience with machine learning and deep neural network techniques. Experience with wearable and sensors placed in the environment. Knowledge of characteristics associated with mild cognitive
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at the intersection of AI, NLP, and industrial applications. Contribute to the development of scalable and interpretable AI tools for real-world deployment. Qualifications: A PhD in Computer Science, Machine Learning
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qualification) in AI (e.g., machine learning, natural language processing or computer vision); A strong scientific track record, documented by publications at first-tier conferences and journals (e.g., NeurIPS
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. Proficiency in Python and/or machine learning applications for data analysis. Ability to work independently and manage multiple research activities. Experience contributing to academic publications and
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residence, to conduct research in Duke's library and archival collections, to participate actively in the intellectual life of the university, to teach up to 2 courses per year, and to give a public lecture